Triple
T1093639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing 787 Dreamliner |
E24221
|
entity |
| Predicate | wingSpan |
P4571
|
FINISHED |
| Object | approximately 60.1 meters |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: approximately 60.1 meters | Statement: [Boeing 787 Dreamliner, wingSpan, approximately 60.1 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wingSpan Context triple: [Boeing 787 Dreamliner, wingSpan, approximately 60.1 meters]
-
A.
wingspan
chosen
Indicates the distance from the tip of one wing to the tip of the other wing when fully extended.
-
B.
wingArea
Indicates the total surface area covered by an entity’s wing or wings.
-
C.
typeOfWing
Indicates the specific kind or category of wing that an entity possesses or is associated with.
-
D.
wingConfiguration
Indicates how the wings of an aircraft or creature are arranged or structured relative to its body and to each other.
-
E.
aircraftLength
Indicates the physical longitudinal measurement of an aircraft from its nose to its tail.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99d1e8c81909cf1178d68d38885 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b743175481908f3967e589717c55 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.